Multi-antenna transmission for spatial division multiple access

ABSTRACT

An uplink channel response matrix is obtained for each terminal and decomposed to obtain a steering vector used by the terminal to transmit on the uplink. An “effective” uplink channel response vector is formed for each terminal based on its steering vector and its channel response matrix. Multiple sets of terminals are evaluated based on their effective channel response vectors to determine the best set (e.g., with highest overall throughput) for uplink transmission. Each selected terminal performs spatial processing on its data symbol stream with its steering vector and transmits its spatially processed data symbol stream to an access point. The multiple selected terminals simultaneously transmit their data symbol streams via their respective MIMO channels to the access point. The access point performs receiver spatial processing on its received symbol streams in accordance with a receiver spatial processing technique to recover the data symbol streams transmitted by the selected terminals.

CLAIM OF PRIORITY

This application is a continuation application of, and claims thebenefit of priority from, U.S. patent application Ser. No. 11/869,457 toWalton, et al., filed on Oct. 9, 2007 and entitled “Multi-AntennaTransmission for Spatial Division Multiple Access”, which is acontinuation application of, and claims the benefit of priority from,U.S. Pat. No. 7,298,805 to Walton, et al., issued Nov. 20, 2007 andentitled “Multi-Antenna Transmission for Spatial Division MultipleAccess”, both of which are assigned to the assignee of this application,and are fully incorporated herein by reference for all purposes.

BACKGROUND

I. Field

The present invention relates generally to data communication, and morespecifically to multi-antenna transmission for spatial division multipleaccess (SDMA) in a multiple-input multiple-output (MIMO) communicationsystem.

II. Background

A MIMO system employs multiple (NT) transmit antennas and multiple (NR)receive antennas for data transmission. A MIMO channel formed by the NTtransmit and NR receive antennas may be decomposed into NS spatialchannels, where N_(S)≦min {N_(T), N_(R)}. The NS spatial channels may beused to transmit NS independent data streams to achieve greater overallthroughput.

In a multiple-access MIMO system, an access point can communicate withone or more user terminals at any given moment. If the access pointcommunicates with a single user terminal, then the NT transmit antennasare associated with one transmitting entity (either the access point orthe user terminal), and the NR receive antennas are associated with onereceiving entity (either the user terminal or the access point). Theaccess point can also communicate with multiple user terminalssimultaneously via SDMA. For SDMA, the access point utilizes multipleantennas for data transmission and reception, and each of the userterminals typically utilizes one antenna for data transmission andmultiple antennas for data reception.

Some key challenges for SDMA in a multiple-access MIMO system are (1)selecting the proper set of user terminals for simultaneous transmissionand (2) transmitting data to and/or from each selected user terminal ina manner to achieve good system performance. There is therefore a needin the art for techniques to efficiently support SDMA for amultiple-access MIMO system.

SUMMARY

Techniques for performing multi-antenna transmission for SDMA in a MIMOsystem are described herein. These techniques may be used in combinationwith various wireless technologies such as Code Division Multiple Access(CDMA), Orthogonal Frequency Division Multiplexing (OFDM), Time DivisionMultiple Access (TDMA), and so on. For uplink transmission by multipleuser terminals to a single access point, an uplink channel responsematrix is obtained for each active user terminal (e.g., a terminaldesiring to transmit on the uplink) and decomposed to obtain a steeringvector for the user terminal. Each user terminal uses its steeringvector for spatial processing to transmit on the uplink, if selected foruplink transmission. An “effective” uplink channel response vector isformed for each user terminal based on the steering vector and theuplink channel response matrix for the user terminal.

For each scheduling interval (e.g., each time slot), multiple sets ofactive user terminals are formed and evaluated based on their effectivechannel response vectors (or their channel response matrices) todetermine the best set of N_(up) user terminals for uplink transmissionin that scheduling interval. For example, the user set with the highestoverall throughput may be selected. In effect, the spatial signatures ofthe user terminals as well as multi-user diversity are exploited toselect a set of “spatially compatible” user terminals for simultaneoustransmission on the uplink, as described below. The same or differentnumber of user terminals may be selected for uplink transmission indifferent scheduling intervals.

Each user terminal selected for uplink transmission processes its datastream in accordance with the underlying wireless technology (e.g.,CDMA, OFDM, or TDMA) to obtain a data symbol stream. Each user terminalfurther performs spatial processing on its data symbol stream with itssteering vector to obtain a set of transmit symbol streams, one transmitsymbol stream for each antenna at the user terminal. Each user terminalthen transmits its transmit symbol streams from its multiple antennasand via its MIMO channel to the access point. The N_(up) selected userterminals simultaneously transmit their N_(up) data symbol streams(e.g., one data symbol stream for each terminal) via their respectiveMIMO channels to the access point. The access point obtains multiplereceived symbol streams from its multiple antennas. The access pointthen performs receiver spatial processing on the received symbol streamsin accordance with a linear or non-linear receiver spatial processingtechnique to recover the N_(up) data symbol streams transmitted by theN_(up) selected user terminals, as described below.

The techniques to support SDMA transmission on the downlink are alsodescribed herein. Various aspects and embodiments of the invention aredescribed in further detail below.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a multiple-access MIMO system;

FIG. 2 shows a process for performing multi-antenna transmission on theuplink for SDMA;

FIG. 3 shows a process for evaluating and selecting user terminals forsimultaneous transmission on the uplink;

FIG. 4 shows a block diagram of an access point and two user terminals;

FIGS. 5A and 5B show block diagrams of transmit (TX) data processors forCDMA and OFDM, respectively;

FIG. 6 shows the spatial processing at the access point and one userterminal for downlink and uplink transmission;

FIG. 7 shows a receive spatial processor and a receive data processor;and

FIG. 8 shows a controller and a scheduler at the access point.

DETAILED DESCRIPTION

The word “exemplary” is used herein to mean “serving as an example,instance, or illustration.” Any embodiment described herein as“exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments.

The multi-antenna transmission techniques described herein may be usedin combination with various wireless technologies such as CDMA, OFDM,TDMA, and so on. Multiple user terminals can concurrentlytransmit/receive data via different (1) orthogonal code channels forCDMA, (2) time slots for TDMA, or (3) subbands for OFDM. A CDMA systemmay implement IS-2000, IS-95, IS-856, Wideband-CDMA (W-CDMA), or someother standards. An OFDM system may implement IEEE 802.11 or some otherstandards. A TDMA system may implement GSM or some other standards.These various standards are known in the art. The spatial processing formulti-antenna transmission may be performed on top of (either before orafter) the data processing for the underlying wireless technology, asdescribed below.

FIG. 1 shows a multiple-access MIMO system 100 with access points anduser terminals. For simplicity, only one access point 110 is shown inFIG. 1. An access point is generally a fixed station that communicateswith the user terminals and may also be referred to as a base station orsome other terminology. A user terminal may be fixed or mobile and mayalso be referred to as a mobile station, a wireless device, or someother terminology. Access point 110 may communicate with one or moreuser terminals 120 at any given moment on the downlink and uplink. Thedownlink (i.e., forward link) is the communication link from the accesspoint to the user terminals, and the uplink (i.e., reverse link) is thecommunication link from the user terminals to the access point. A userterminal may also communicate peer-to-peer with another user terminal. Asystem controller 130 couples to and provides coordination and controlfor the access points.

System 100 employs multiple transmit and multiple receive antennas fordata transmission on the downlink and uplink. Access point 110 isequipped with Nap antennas and represents the multiple-input (MI) fordownlink transmissions and the multiple-output (MO) for uplinktransmissions. A set of N_(u) selected user terminals 120 collectivelyrepresents the multiple-output for downlink transmissions and themultiple-input for uplink transmissions. For pure SDMA, it is desired tohave N_(ap)≧N_(u)≧1 if the data symbol streams for the N_(u) userterminals are not multiplexed in code, frequency, or time by some means.N_(u) may be greater than Nap if the data symbol streams can bemultiplexed using different code channels with CDMA, disjoint sets ofsubbands with OFDM, and so on. Each selected user terminal transmitsuser-specific data to and/or receives user-specific data from the accesspoint. In general, each selected user terminal may be equipped with oneor multiple antennas (i.e., N_(ut)≧1). The N_(u) selected user terminalscan have the same or different number of antennas.

System 100 may be a time division duplex (TDD) system or a frequencydivision duplex (FDD) system. For a TDD system, the downlink and uplinkshare the same frequency band. For an FDD system, the downlink anduplink use different frequency bands. MIMO system 100 may also utilize asingle carrier or multiple carriers for transmission. For simplicity,the following description assumes that (1) system 100 is asingle-carrier system and (2) each user terminal is equipped withmultiple antennas. For clarity, data transmission on the uplink isdescribed below.

An uplink MIMO channel formed by the Nap antennas at the access pointand the N_(ut,m) antennas at a given user terminal m may becharacterized by an N_(ap)×N_(ut,m) channel response matrix H _(up,m),which may be expressed as:

$\begin{matrix}{{{\underset{\_}{H}}_{{up},m} = \begin{bmatrix}h_{1,1} & h_{1,2} & \ldots & h_{1,N_{{ut},m}} \\h_{2,1} & h_{2,2} & \ldots & h_{2,N_{{ut},m}} \\\vdots & \vdots & \ddots & \vdots \\h_{N_{ap},1} & h_{N_{ap},2} & \ldots & h_{N_{ap},N_{{ut},m}}\end{bmatrix}},} & {{Eq}\mspace{14mu} (1)}\end{matrix}$

-   where entry h_(i,j), for i=1 . . . N_(ap) and j=1 . . . N_(ut,m), is    the coupling (i.e., complex gain) between access point antenna i and    user terminal antenna j.    For simplicity, the MIMO channel is assumed to be non-dispersive    (i.e., flat fading), and the coupling between each transmit and    receive antenna pair is represented with a single complex gain    h_(i,j). In general, each user terminal is associated with a    different uplink channel response matrix having dimensions    determined by the number of antennas at that user terminal.

The uplink channel response matrix H _(ap,m) for user terminal m may be“diagonalized” using either singular value decomposition or eigenvaluedecomposition to obtain Nm eigenmodes of H _(up,m). The singular valuedecomposition of H _(up,m) may be expressed as:

H _(up,m)=U _(up,m) Σ _(up,m) V _(up,m) ^(H),   Eq (2)

where U _(up,m) is an N_(ap)×N_(ap) unitary matrix of left eigenvectorsof H _(up,m);

-   -   Σ _(up,m) is an N_(ap)×N_(ut,m) diagonal matrix of singular        values of H _(up,m);    -   V _(up,m) is an N_(ut,m)×N_(ut,m) unitary matrix of right        eigenvectors of H _(up,m); and    -   “H” denotes the conjugate transpose.        A unitary matrix M is characterized by the property M ^(H) M=I,        where I is the identity matrix. The columns of a unitary matrix        are orthogonal to one another.

The eigenvalue decomposition of a correlation matrix of H _(up,m) may beexpressed as:

R _(up,m)=H _(up,m) ^(H) H _(up,m)=V _(up,m) Λ _(up,m) V _(up,m) ^(H),  Eq (3)

where R _(up,m) is the N_(ut,m)×N_(ut,m) correlation matrix of H_(up,m); and

-   -   Λ _(up,m) is an N_(ut,m)×N_(ut,m) diagonal matrix of eigenvalues        of R _(up,m).        Singular value decomposition and eigenvalue decomposition are        known in the art and described, for example, by Gilbert Strang        in “Linear Algebra and Its Applications,” Second Edition,        Academic Press, 1980.

As shown in equations (2) and (3), the columns of V _(up,m) are theright eigenvectors of H _(up,m) as well as the eigenvectors of R_(up,m). The right eigenvectors of H _(up,m) are also referred to as“steering” vectors and may be used for spatial processing by userterminal m to transmit data on the Nm eigenmodes of H _(up,m). Theeigenmodes may be viewed as orthogonal spatial channels obtained throughdecomposition.

The diagonal matrix Σ _(up,m) contains non-negative real values alongthe diagonal and zeros elsewhere. These diagonal entries are known asthe singular values of H _(up,m) and represent the channel gains for theNm eigenmodes of H _(up,m). The singular values in Σ _(up,m) are alsothe square roots of the eigenvalues in Λ _(up,m). The singular values inΣ _(up,m) may be ordered from largest to smallest, and the eigenvectorsin V _(up,m) may be ordered correspondingly. The principal (i.e.,dominant) eigenmode is the eigenmode associated with the largestsingular value in Σ _(up,m), which is the first singular value after theordering. The eigenvector for the principal eigenmode of H _(up,m) isthe first column of V _(up,m) after the ordering and is denoted as v_(up,m).

In a practical system, only an estimate of H _(up,m) can be obtained,and only estimates of V _(up,m), Σ _(up,m) and U _(up,m) can be derived.For simplicity, the description herein assumes channel estimation anddecomposition without errors.

With SDMA, N_(up) user terminals can transmit data concurrently on theuplink to the access point. Each user terminal performs spatialprocessing on its data using a steering vector, which may be derived (1)based on the eigenvector v _(up,m) for the principal eigenmode of thewireless channel for that terminal or (2) in some other manner. Each ofthe N_(up) user terminals can transmit data on the principal eigenmodeof its uplink MIMO channel using either “beam-forming” or“beam-steering”, as described below.

1. Beam-Forming

For beam-forming, each user terminal m spatially processes its datasymbol stream {s_(up,m)} with its steering vector V _(up,m) to obtainN_(ut,m) transmit symbol streams, as follows:

x _(up,m) =v _(up,m) ·s _(up,m),   Eq (4)

where s_(up,m) is a data symbol to be transmitted by user terminal m;and

-   -   x _(up,m) is an N_(ut,m)×1 vector with N_(ut,m) transmit symbols        to be sent from the N_(ut,m) antennas at user terminal m.        As used herein, a “data symbol” refers to a modulation symbol        for data, and a “pilot symbol” refers to a modulation symbol for        pilot. Although not shown in equation (4) for simplicity, each        user terminal m may further scale each of the N_(ut,m) transmit        symbols in the vector x _(up,m) with a scaling factor G_(m) such        that the total energy for the N_(ut,m) transmit symbols is unity        or some other selected value. Each user terminal m transmits its        N_(ut,m) transmit symbol streams via its uplink MIMO channel to        the access point.

At the access point, the received symbols obtained for each userterminal m may be expressed as:

r _(up,m) =H _(up,m) x _(up,m) +n _(up,m) =H _(up,m) v _(up,m) s _(up,m)+n _(up,m) =h _(up,eff,m) s _(up,m) +n _(up,m),   Eq (5)

where r _(up,m) is an N_(ap)×1 vector with N_(ap) received symbolsobtained from the N_(ap) access point antennas for user terminal m;

-   -   h _(up,eff,m) is an N_(ap)×1 “effective” uplink channel response        vector for user terminal m, which is h _(up,eff,m)=H _(up,m) v        _(up,m); and    -   n _(up,m) is an N_(ap)×1 noise vector for user terminal m.        The spatial processing by each user terminal m effectively        transforms its MIMO channel with a channel response matrix of H        _(up,m) into a single-input multiple-output (SIMO) channel with        a channel response vector of h _(up,eff,m).

The received symbols at the access point for all N_(up) user terminalstransmitting simultaneously may be expressed as:

$\begin{matrix}\begin{matrix}{{\underset{\_}{r}}_{up} = {{{\underset{\_}{H}}_{{up},{eff}}{\underset{\_}{s}}_{up}} + {\underset{\_}{n}}_{up}}} \\{= {\sum\limits_{m = 1}^{N_{up}}{\underset{\_}{r}}_{{up},m}}} \\{{= {{\sum\limits_{m = 1}^{N_{up}}{{\underset{\_}{h}}_{{up},{eff},m}s_{{up},m}}} + {\underset{\_}{n}}_{{up},m}}},}\end{matrix} & {{Eq}\mspace{14mu} (6)}\end{matrix}$

where s _(up) is an N_(up)×1 vector with N_(up) data symbols transmittedby the N_(up) user terminals, which is s _(up)=[s_(up,1) s_(up,2) . . .s_(up,N) _(up) ]^(T);

-   -   H _(up,eff) is an N_(ap)×N_(up) effective uplink channel        response matrix for all N_(up) user terminals, which is H        _(up,eff)=[h _(up,eff,1) h _(up,eff,2) . . . h _(up,eff,N) _(up)        ]; and    -   n _(up) is an N_(ap)×1 noise vector at the access point.

The access point can recover the N_(up) data symbol streams transmittedby the N_(up) user terminals using various receiver processingtechniques such as a channel correlation matrix inversion (CCMI)technique (which is also commonly referred to as a zero-forcingtechnique), a minimum mean square error (MMSE) technique, a successiveinterference cancellation (SIC) technique, and so on.

A. CCMI Spatial Processing

For the CCMI technique, the access point performs receiver spatialprocessing as follows:

$\begin{matrix}\begin{matrix}{{{\underset{\_}{\hat{s}}}_{c\; c\; m\; i} = {{\underset{\_}{M}}_{c\; c\; m\; i}{\underset{\_}{r}}_{up}}},} \\{{= {{\underset{\_}{R}}_{{up},{eff}}^{- 1}{{\underset{\_}{H}}_{{up},{eff}}^{H}( {{{\underset{\_}{H}}_{{up},{eff}}{\underset{\_}{s}}_{up}} + {\underset{\_}{n}}_{up}} )}}},} \\{{= {{\underset{\_}{s}}_{up} + {\underset{\_}{n}}_{c\; c\; m\; i}}},}\end{matrix} & {{Eq}\mspace{14mu} (7)}\end{matrix}$

where M _(ccmi) is an N_(up)×N_(ap) spatial filter matrix for the CCMItechnique, which is M _(ccmi)=R _(up,eff) ⁻¹ H _(up,eff) ^(H), where R_(up,eff)=H _(up,eff) ^(H) H _(up,eff);

-   -   ŝ _(ccmi) is an N_(up)×1 vector with N_(up) recovered data        symbols for the N_(up) user terminals with the CCMI technique;        and    -   n _(ccmi)=M _(ccmi) n _(up) is the CCMI filtered noise.

For simplicity, the noise n _(up) is assumed to be additive whiteGaussian noise (AWGN) with zero mean, a variance of σ_(n) ², and anautocovariance matrix of φ _(nn)=E[n _(up) n _(up) ^(H)]=σ_(n) ² I,where E[x] is the expected value of x. In this case, thesignal-to-noise-and-interference ratio (SNR) of the recovered datasymbol stream {ŝ_(ccmi,m)} for each user terminal m may be expressed as:

$\begin{matrix}\begin{matrix}{{\gamma_{{c\; c\; m\; i},m} = \frac{P_{{ut},m}}{r_{m\; m}\sigma_{n}^{2}}},} & {{{{for}\mspace{14mu} m} = {1\mspace{14mu} \ldots \mspace{14mu} N_{up}}},}\end{matrix} & {{Eq}\mspace{14mu} (8)}\end{matrix}$

where P_(ut,m) is the transmit power used by user terminal m;

-   -   r_(mm) is the m-th diagonal element of R _(up,eff); and    -   γ_(ccmi,m) is the SNR for user terminal m with the CCMI        technique.        Due to the structure of R _(up,eff), the CCMI technique may        amplify the noise.

B. MMSE Spatial Processing

For the MMSE technique, a spatial filter matrix M _(mmse) is derivedsuch that the mean square error between the estimated data vector fromthe MMSE spatial filter and the data vector s _(up) is minimized. ThisMMSE criterion may be expressed as:

$\begin{matrix}{{\min\limits_{{\underset{\_}{M}}_{m\; m\; s\; e}}{E\lbrack {( {{{\underset{\_}{M}}_{m\; m\; s\; e}{\underset{\_}{r}}_{up}} - {\underset{\_}{s}}_{up}} )^{H}( {{{\underset{\_}{M}}_{m\; m\; s\; e}{\underset{\_}{r}}_{up}} - {\underset{\_}{s}}_{up}} )} \rbrack}},} & {{Eq}\mspace{14mu} (9)}\end{matrix}$

where M _(mmse) is the N_(up)×N_(ap) spatial filter matrix for the MMSEtechnique.

The solution to the optimization problem posed in equation (9) may beobtained in various manners. In one exemplary method, the MMSE spatialfilter matrix M _(mmse) is derived as:

M _(mmse) =H _(up,eff) ^(H) [H _(up,eff) H _(up,eff) ^(H)+σ_(n) ² I] ⁻¹.  Eq (10)

The spatial filter matrix M _(mmse) contains N_(up) rows for N_(up) MMSEspatial filter row vectors for the N_(up) user terminals. The MMSEspatial filter row vector for each user terminal may be expressed as m_(mmse,m)=h _(up,eff,m) ^(H) G. where G=[H _(up,eff) H _(up,eff)^(H)+σ_(n) ² I]¹.

The access point performs receiver spatial processing as follows:

$\begin{matrix}\begin{matrix}{{{\underset{\_}{\hat{s}}}_{m\; m\; s\; e} = {{\underset{\_}{D}}_{m\; m\; s\; e}^{- 1}{\underset{\_}{M}}_{m\; m\; s\; e}{\underset{\_}{r}}_{up}}},} \\{{= {{\underset{\_}{D}}_{m\; m\; s\; e}^{- 1}{{\underset{\_}{M}}_{m\; m\; s\; e}( {{{\underset{\_}{H}}_{{up},{eff}}{\underset{\_}{s}}_{up}} + {\underset{\_}{n}}_{up}} )}}},} \\{{= {{\underset{\_}{s}}_{up} + {\underset{\_}{n}}_{m\; m\; s\; e}}},}\end{matrix} & {{Eq}\mspace{14mu} (11)}\end{matrix}$

where D _(mmse) is an N_(up)×N_(up) diagonal matrix whose diagonalelements are the diagonal elements of M _(mmse) H _(up,eff), i.e., D_(mmse)=diag [M _(mmse) H _(up,eff)];

-   -   ŝ _(mmse) is an N_(up)×1 recovered data symbol vector for the        MMSE technique; and    -   n _(mmse)=M _(mmse) n _(up) is the MMSE filtered noise.        In equation (11), the MMSE spatial filter provides an        unnormalized estimate of s _(up), and the scaling by the        diagonal matrix D _(mmse) ⁻¹ provides a normalized estimate of s        _(up).

The SNR of the recovered data symbol stream {ŝ_(mmse,m)} for each userterminal m may be expressed as:

$\begin{matrix}\begin{matrix}{{\gamma_{{m\; m\; s\; e},m} = \frac{q_{m\; m}}{1 - q_{m\; m}}},} & {{{{for}\mspace{14mu} m} = {1\mspace{14mu} \ldots \mspace{14mu} N_{up}}},}\end{matrix} & {{Eq}\mspace{14mu} (12)}\end{matrix}$

where q_(mm) is the m-th diagonal element of M _(mmse) H _(up,eff),i.e., q_(mm)=m _(mmse,m) h _(up,eff,m); and

-   -   γ_(mmse,m) is the SNR for user terminal m with the MMSE        technique.

C. Successive Interference Cancellation Spatial Processing

The access point can process the N_(ap) received symbol streams usingthe SIC technique to recover the N_(up) data symbol streams. For the SICtechnique, the access point initially performs spatial processing on theN_(ap) received symbol streams (e.g., using CCMI, MMSE, or some othertechnique) and obtains one recovered data symbol stream. The accesspoint then processes (e.g., demodulates/symbol demaps, deinterleaves,and decodes) this recovered data symbol stream to obtain a decoded datastream. The access point next estimates the interference this streamcauses to the other N_(up)−1 data symbol streams and cancels theestimated interference from the N_(ap) received symbol streams to obtainN_(ap) modified symbol streams. The access point then repeats the sameprocessing on the N_(ap) modified symbol streams to recover another datasymbol stream.

For the SIC technique, the input (i.e., received or modified) symbolstreams for stage l, where l=1 . . . N_(up), may be expressed as:

r _(sic) ^(l)(k)= H _(up,eff) ^(l) s _(up) ^(l) +n _(up) ^(l),   Eq (13)

where r _(sic) ^(l) is an N_(ap)×1 vector with N_(ap) input symbols forstage l, and r _(sic) ¹=r _(up) for the first stage;

-   -   s _(up) ^(l) is an N_(nr)×1 vector for N_(nr) data symbol        streams not yet recovered at stage l, where N_(nr)=N_(up)−l+1;        and    -   H _(up,eff) ^(l) is an N_(ap)×N_(nr) reduced effective channel        response matrix for stage l.

Equation (13) assumes that the data symbol streams recovered in the l−1prior stages are canceled. The dimensionality of the effective channelresponse matrix H _(up,eff) successively reduces by one column for eachstage as a data symbol stream is recovered and canceled. For stage l,the reduced effective channel response matrix H _(up,eff) ^(l) isobtained by removing l−1 columns in the original matrix H _(up,eff)corresponding to the l−1 data symbol streams already recovered in priorstages, i.e., H _(up,eff) ^(l)=[h _(up,eff,j) _(l) h _(up,eff,j) _(l+1). . . h _(up,eff,j) _(h) _(up,eff,) _(j N up) ], where h _(up,eff,j)_(n) is an N_(ap)×1 effective channel response vector for user terminalj_(n). For stage l, the l−1 data symbol streams recovered in the priorstages are given indices of {j₁ j₂ . . . j_(l−1)}, and the N_(nr) datasymbol streams not yet recovered are given indices of {j_(l) j_(l+1) . .. j_(N) _(up) }.

For stage l, the access point derives an N_(nr)×N_(ap) spatial filtermatrix M _(sic) ^(l) based on the reduced effective channel responsematrix H _(up,eff) ^(l) (instead of the original matrix H _(up,eff))using the CCMI, MMSE, or some other technique. Since H _(up,eff) ^(l) isdifferent for each stage, the spatial filter matrix M _(sic) ^(l) isalso different for each stage.

The access point multiplies the vector r _(sic) ^(l) for the N_(ap)modified symbol streams with the spatial filter matrix M _(sic) ^(l) toobtain a vector {tilde over (s)} _(sic) ^(l) for N_(nr) detected symbolstreams, as follows:

$\begin{matrix}\begin{matrix}{{{\underset{\_}{\overset{\sim}{s}}}_{sic}^{l} = {{\underset{\_}{M}}_{sic}^{l}{\underset{\_}{r}}_{sic}^{l}}},} \\{= {{\underset{\_}{M}}_{sic}^{l}( {{{\underset{\_}{H}}_{{up},{eff}}^{l}{\underset{\_}{s}}_{up}^{l}} + {\underset{\_}{n}}_{up}} )}} \\{{= {{{\underset{\_}{Q}}_{sic}^{l}{\underset{\_}{s}}_{up}^{l}} + {\underset{\_}{n}}_{sic}^{l}}},}\end{matrix} & {{Eq}\mspace{14mu} (14)}\end{matrix}$

where Q _(sic) ^(l)=M _(sic) ^(l) H _(up,eff) ^(l) and n _(sic) ^(l)=M_(sic) ^(l) n is the filtered noise for stage l. The access point thenselects one of the N_(nr) detected symbol streams for recovery, wherethe selection criterion may be based on SNR and/or other factors. Forexample, the detected symbol stream with the highest SNR among theN_(nr) detected symbol streams may be selected for recovery. Since onlyone data symbol stream is recovered in each stage, the access point cansimply derive one 1×N_(ap) spatial filter row vector m _(j) _(l) ^(l)for the data symbol stream {s_(up,j) _(l) } to be recovered in stage l.The row vector m _(j) _(l) ^(l) is one row of the matrix M _(sic) ^(l).In this case, the spatial processing for stage l to recover the datasymbol stream {s_(up,j) _(l) } may be expressed as:

{tilde over (s)} _(up,j) _(l) =m _(j) _(l) ^(l) r _(sic) ^(l) =q _(j)_(l) ^(l) s _(up) ^(l) +m _(j) _(l) ^(l) n _(up),   Eq (15)

where q _(j) _(l) ^(l) is the row of Q _(sic) ^(l) corresponding to datasymbol stream {s_(up,j) _(l) }.

In any case, the access point scales the detected symbol stream {{tildeover (s)}_(up,j) _(l) } to obtain a recovered data symbol stream{ŝ_(up,j) _(l) } and further demodulates, deinterleaves, and decodesthis stream {ŝ_(up,j) _(l) } to obtain a decoded data stream{{circumflex over (d)}_(up,j) _(l) }. The access point also forms anestimate of the interference this stream causes to the other data symbolstreams not yet recovered. To estimate the interference, the accesspoint re-encodes, interleaves, and modulates the decoded data stream{{circumflex over (d)}_(up,j) _(l) } in the same manner as performed atuser terminal j_(l) and obtains a stream of “remodulated” symbols{{tilde over (s)}_(up,j) _(l) }, which is an estimate of the data symbolstream {s_(up,j) _(l) } just recovered. The access point then spatiallyprocesses the remodulated symbol stream with the effective channelresponse vector h _(up,eff,j) _(l) for user terminal j_(l) to obtain avector i _(j) _(l) with N_(ap) interference components caused by thisstream. The N_(ap) interference components i _(j) _(l) are thensubtracted from the N_(ap) modified symbol streams r _(sic) ^(l) forstage l to obtain N_(ap) modified symbol streams r _(sic) ^(l|1) for thenext stage l+1, i.e., r _(sic) ^(l+1)=r _(sic) ^(l)−i_(j) _(l) . Themodified symbol streams r _(sic) ^(l+1) represent the streams that wouldhave been received by the access point if the data symbol stream{s_(up,j) _(l) } had not been transmitted (i.e., assuming that theinterference cancellation was effectively performed).

The access point processes the N_(ap) received symbol streams in N_(up)successive stages. For each stage, the access point (1) performsreceiver spatial processing on either the N_(ap) received symbol streamsor the N_(ap) modified symbol streams from the preceding stage to obtainone recovered data symbol stream, (2) processes this recovered datasymbol stream to obtain a corresponding decoded data stream, (3)estimates and cancels the interference due to this stream, and (4)obtains N_(ap) modified symbol streams for the next stage. If theinterference due to each data stream can be accurately estimated andcanceled, then later recovered data streams experience less interferenceand may be able to achieve higher SNRs.

For the SIC technique, the SNR of each recovered data symbol stream isdependent on (1) the spatial processing technique (e.g., CCMI or MMSE)used for each stage, (2) the specific stage in which the data symbolstream is recovered, and (3) the amount of interference due to datasymbol streams recovered in subsequent stages. In general, the SNRprogressively improves for data symbol streams recovered in later stagesbecause the interference from data symbol streams recovered in priorstages is canceled. This then allows higher rates to be used for datasymbol streams recovered later.

2. Beam-Steering

For beam-steering, each user terminal m performs spatial processing witha normalized steering vector {tilde over (v)} _(up,m), which is derivedusing the phase information in the steering vector v _(up,m). Thenormalized steering vector {tilde over (v)} _(up,m) may be expressed as:

{tilde over (v)} _(up,m)=[Ae^(jθ) ^(m,1) Ae^(jθ) ^(m,2) . . . Ae^(jθ)^(m,N) _(ut) ]^(T),   Eq (16)

where A is a constant (e.g., A=1/√{square root over (N_(ut,m))}); and

-   -   θ_(m,i) is the phase for antenna i at user terminal m, which is:

$\begin{matrix}{\theta_{m,i} = {{\angle \; v_{{up},m,i}} = {{\tan^{- 1}( \frac{{Im}\{ v_{{up},m,i} \}}{{Re}\{ v_{{up},m,i} \}} )}.}}} & {{Eq}\mspace{14mu} (17)}\end{matrix}$

As shown in equation (16), the N_(ut,m) elements of {tilde over (v)}_(up,m) have equal magnitude. As shown in equation (17), the phase ofeach element in {tilde over (v)} _(up,m) is equal to the phase of acorresponding element in v _(up,m) (i.e., θ_(m,i) is obtained fromv_(up,m,i), where v _(up,m)=[v_(up,m,1) v_(up,m,2) . . . v_(up,m,N)_(ut) ]^(T)).

Each user terminal m spatially processes its data symbol stream{s_(up,m)} with its normalized steering vector {tilde over (v)} _(up,m)to obtain N_(ut,m) transmit symbol streams, as follows:

{tilde over (x)} _(up,m) ={tilde over (v)} _(up,m) ·s _(up,m).   Eq (18)

The constant A in equation (16) may be selected such that the totalenergy of the N_(ut,m) transmit symbols in the vector {tilde over (x)}_(up,m) is unity or some other selected value. The N_(ap)×1 effectiveuplink channel response vector {tilde over (h)} _(up,eff,m) for eachuser terminal m with beam-steering may be expressed as:

{tilde over (h)} _(up,eff,m)=H _(up,m) {tilde over (v)} _(up,m).   Eq(19)

The N_(ap)×N_(up) effective uplink channel response matrix {tilde over(H)} _(up,eff) for all N_(up) user terminals for beam-steering is then{tilde over (H)} _(up,eff)=[{tilde over (h)} _(up,eff,1) {tilde over(h)} _(up,eff,2) . . . {tilde over (h)} _(up,eff,N) _(up) ].

The access point can perform receiver spatial processing using the CCMI,MMSE, or SIC technique described above, or some other technique.However, the spatial filter matrix is derived with the matrix {tildeover (H)} _(up,eff) instead of the matrix H _(up,eff).

3. SDMA Transmission

FIG. 2 shows a process 200 for performing multi-antenna transmission onthe uplink for SDMA. Initially, an uplink channel response matrix H_(up,m) is obtained for each active user terminal desiring to transmiton the uplink (block 210). The matrix H _(up,m) for each user terminalis decomposed to obtain a steering vector v _(up,m) or {tilde over (v)}_(up,m) for the user terminal (block 212). An effective uplink channelresponse vector h _(up,eff,m) is formed for each user terminal based onthe steering vector and the uplink channel response matrix for the userterminal (block 214). Blocks 210 through 214 are for channel estimationand decomposition and may be performed by the access point, the userterminals, or both.

Different sets of active user terminals are formed and evaluated basedon their effective uplink channel response vectors h _(up,eff,m) ortheir uplink channel response matrices H _(up,m) (block 220). Theevaluation may be performed as described below. The best set of Nup userterminals is selected for transmission (also block 220). The rate to useby each selected user terminal (which is obtained from the evaluation inblock 220) is sent to the user terminal (block 222). Blocks 220 and 222are for user scheduling and are typically performed by the access point.

Each selected user terminal performs spatial processing on its datasymbol stream {s_(up,m)} with its steering vector v _(up,m) or {tildeover (v)} _(up,m) and transmits N_(ut,m) transmit symbol streams fromits N_(ut,m) antennas and via its MIMO channel to the access point(block 230). The N_(up) selected user terminals simultaneously transmittheir N_(up) data symbol streams via their MIMO channels to the accesspoint. Block 230 is for data transmission and is performed by eachselected user terminal.

The access point obtains Nap received symbol streams from its Napantennas (block 240). The access point then performs receiver spatialprocessing on the Nap received symbol streams in accordance with theCCMI, MMSE, SIC, or some other technique to obtain N_(up) recovered datasymbol streams, which are estimates of the N_(up) data symbol streamstransmitted by the N_(up) selected user terminals (block 242). Blocks240 and 242 are for data reception and are performed by the accesspoint.

Multiple user terminals can be selected for simultaneous transmission onthe uplink. The user selection may be based on various factors. Somefactors may relate to system constraints and requirements such asquality of service, maximum latency, average data rate, and so on. Thesefactors may need to be satisfied for each user terminal. Other factorsmay relate to system performance, which may be quantified by overallsystem throughput or some other indication of performance. A schedulingscheme can evaluate user terminals for transmission based on one or moremetrics and one or more factors. Different scheduling schemes may usedifferent metrics, take into account different factors, and/or weigh themetrics and factors differently.

Regardless of the particular scheduling scheme selected for use,different sets of user terminals can be evaluated in accordance with thescheduling scheme. The “spatial signatures” of the individual userterminals (e.g., their MIMO channel responses) and multi-user diversitycan be exploited to select the “best” set of “spatially compatible” userterminals for simultaneous transmission. Spatial compatibility may bequantified by a metric such as overall throughput or some other measureof performance. The best user set may be the one that achieves thehighest score for the metric (e.g., the highest overall throughput)while conforming to the system constraints and requirements.

For clarity, a specific scheduling scheme that selects user terminalsbased on overall throughput is described below. In the followingdescription, N_(act) user terminals are active and desire to transmitdata on the uplink.

FIG. 3 shows a process 220 a for evaluating and selecting user terminalsfor transmission on the uplink. Process 220 a represents a specificscheduling scheme and may be used for block 220 in FIG. 2. Initially, avariable R_(max) for the highest overall throughput is set to zero(block 310).

A new set of user terminals is selected from among the N_(act) activeuser terminals (block 312). This user set forms a hypothesis to beevaluated and is denoted as u _(n)={u_(n,1) u_(n,2) . . . u_(n,N) _(up)}, where n denotes the n-th user set being evaluated and u_(n,i) is thei-th user terminal in set n. An effective uplink channel response matrixH _(up,eff,n) is formed for user set n with the effective uplink channelresponse vectors h _(up,eff,u) _(n,1) through h _(up,eff,u) _(n,N) ^(up)for the N_(up) user terminals in set n (block 314).

The SNR for each user terminal in set n is then computed based on theeffective uplink channel response matrix H _(up,eff,n) and using theCCMI, MMSE, SIC, or some other technique employed by the access point(block 316). The SNRs for the user terminals with the CCMI and MMSEtechniques can be computed as shown in equations (8) and (12),respectively. The SNRs for the user terminals with the SIC technique aredependent on the order in which the user terminals are recovered. Forthe SIC technique, one or multiple orderings of user terminals may beevaluated. For example, a specific ordering may be evaluated whereby theuser terminal with the highest SNR at each stage is processed by theaccess point. In any case, the SNRs for the N_(up) user terminals in setn are denoted as {γ_(n,1) γ_(n,2) . . . γ_(n,N) _(up) }.

The throughput for each user terminal in set n is then computed based onthe SNR for the user terminal (block 318), as follows:

$\begin{matrix}\begin{matrix}{{r_{n,i} = {\cdot {\log_{2}( {1 + \frac{\gamma_{n,i}}{c_{n,i}}} )}}},} & {{{{for}\mspace{14mu} i} = {1\mspace{14mu} \ldots \mspace{14mu} N_{up}}},}\end{matrix} & {{Eq}\mspace{14mu} (20)}\end{matrix}$

where c_(n,i) is a positive constant that reflects the fraction of thetheoretical capacity achieved by the coding and modulation schemes to beused by user terminal u_(n,i) (e.g., c_(n,i)=2 for a coding andmodulation scheme that is 3 dB from Shannon capacity) and r_(n,i) is thethroughput or spectral efficiency for user terminal u_(n,i) given inunits of bits per second per Hertz (bps/Hz). The overall throughputR_(n) achieved by user set n can be computed (block 320), as follows:

$\begin{matrix}{R_{n} = {\sum\limits_{i = 1}^{N_{up}}{r_{n,i}.}}} & {{Eq}\mspace{14mu} (21)}\end{matrix}$

A determination is then made whether or not the overall throughput R_(n)for user set n is greater than the maximum overall throughput achievedthus far for all user sets that have been evaluated (block 330). If theanswer is yes, then user set n and the overall throughput R_(n) for thisset are saved (block 332). Otherwise, user set n is discarded.

A determination is then made whether or not all user sets have beenevaluated (block 340). If the answer is no, then the process returns toblock 312 to select another set of user terminals for evaluation.Otherwise, the user terminals in the saved set are scheduled fortransmission on the uplink (block 342).

For the embodiment described above, a metric based on theoreticalcapacity (albeit with a compensation factor c_(n,i)) is used to selectthe best user set for uplink transmission. In another embodiment, ametric based on realizable throughput is used to select the best userset. For this embodiment, the user sets may be evaluated based on a setof “rates” supported by the system. These rates may be viewed asquantized values of the throughputs computed in equation (20). Eachnon-zero rate is associated with specific coding and modulation schemes,a particular spectral efficiency (which is typically given in units ofbps/Hz), and a particular required SNR. The required SNR for each ratemay be determined by computer simulation, empirical measurement, and soon, and based on an assumption of an AWGN channel. A look-up table (LUT)can store the set of supported rates and their required SNRs. The SNRfor each user terminal is mapped to a selected rate, which is thehighest rate in the look-up table with a required SNR that is equal toor lower than the SNR for the user terminal. The selected rates for alluser terminals in each set are accumulated to obtain an aggregate ratefor the set. The user set with the highest aggregate rate is scheduledfor transmission.

User sets of different sizes may be evaluated to determine the best userset for transmission. For example, sets with one user terminal (i.e.,N_(up)=1) may be evaluated first, then sets with two user terminals(i.e., N_(up)=2) may be evaluated next, and so on, and sets with N_(ap)user terminals (i.e., N_(up)=N_(ap)) may be evaluated last.

Depending on the values for N_(up), N_(act) and N_(ap), a large numberof user sets may need to be evaluated for an exhaustive search for thebest user set. The number of user sets to evaluate may be reduced byprioritizing the active user terminals, considering other factors, andso on. The priority of each active user terminal may be determined basedon various factors such as the service category for the user terminal(e.g., premium or normal), the average throughput achieved by the userterminal, the amount of data the user terminal has to send, the delayexperienced by the user terminal, and so on. The priority of each userterminal may be updated over time to reflect the current status of theuser terminal. As an example, only the N_(ap) highest priority userterminals may be evaluated in each scheduling interval.

In the exemplary scheduling scheme described above for FIG. 3, theeffective uplink channel response vector h _(up,eff,u) _(n,i) is derivedindependently (or “locally”) for each user terminal based only on theuplink channel response matrix H _(up,u) _(n,i) for the user terminal.The effective channel response matrix H _(up,eff,n) for each user set nis formed with the independently derived effective channel responsevectors for the user terminals in the set. The vectors h _(up,eff,u)_(n,i) , for i=1 . . . N_(up), in the matrix H _(up,eff,n) may not yieldthe highest possible overall throughput for user set n. Multiplesub-hypotheses may be evaluated for each user set, where the vectors inH _(up,eff,n) may be adjusted by different amounts for eachsub-hypothesis. For example, the phases of the steering vectors for theuser terminals in set n may be modified in a deterministic manner (e.g.,by some±percentage) or in a pseudo-random manner for each sub-hypothesiswhile maintaining the power of each steering vector at unity (i.e., aunit norm for each steering vector).

A scheduling scheme may also evaluate each user set n based on theuplink MIMO channel response matrices H _(up,u) _(n,i) instead of theeffective uplink channel response vectors h _(up,eff,u) _(n,i) for theuser terminals in the set. A steering vector v′ _(up,u) _(n,i) may bederived (“globally”) for each user terminal in set n in the presence ofall user terminals in the set. The effective uplink channel responsevector h′ _(up,eff,u) _(n,i) for each user terminal can be computedbased on the (globally derived) steering vector v′ _(up,u) _(n,i) andthe uplink channel response matrix H _(up,u) _(n,i) as follows: h′_(up,eff,u) _(n,i) =H _(up,u) _(n,i) v′ _(up,u) _(n,i) . An effectiveuplink channel response matrix H′ _(up,eff,n) is then formed for userset n based on the effective uplink channel response vectors h′_(up,eff,u) _(n,i) for the user terminals in the set. The performance(e.g., overall throughput) of user set n is then evaluated with thematrix H′ _(up,eff,n) (instead of the matrix H _(up,eff,n)). As anexample, multiple sub-hypotheses may be evaluated for user set n, whereeach sub-hypothesis corresponds to a different set of steering vectorsfor the user terminals in the set. The best sub-hypothesis is thenselected for user set n. Multiple user sets may be evaluated in similarmanner and the best user set is selected for uplink transmission.

Various other scheduling schemes may also be implemented and this iswithin the scope of the invention. Different scheduling schemes mayconsider different factors in selecting the user terminals for each set,derive the steering vectors for the user terminals in different manners,use other metrics to quantify the performance of each user set, and soon.

The uplink channel response matrix H _(up,m) for each user terminal mmay be estimated in various manners. Different channel estimationtechniques may be used for TDD and FDD systems.

In an FDD system, the downlink and uplink use different frequency bands.The channel response for one link may not be correlated with the channelresponse for the other link. In this case, the access point can estimatethe uplink MIMO channel response for each user terminal based on a pilottransmitted by the user terminal. The access point can performdecomposition of H _(up,m) for each user terminal, derive the steeringvector v _(up,m) or {tilde over (v)} _(up,m), and send the steeringvector to each user terminal selected for transmission.

For the FDD system, each user terminal m can transmit an unsteered pilot(or a MIMO pilot) to allow the access point to estimate the uplink MIMOchannel response and obtain the matrix H _(up,m). The unsteered pilotcomprises N_(ut,m) orthogonal pilot transmissions sent from N_(ut,m)user terminal antennas, where orthogonality may be achieved in time,frequency, code, or a combination thereof. For code orthogonality, userterminal m sends N_(ut,m) pilot transmissions simultaneously from itsN_(ut,m) antennas, with the pilot transmission from each antenna being“covered” with a different orthogonal (e.g., Walsh) sequence. The accesspoint “decovers” the received pilot symbols from each access pointantenna i with the same N_(ut,m) orthogonal sequences used by userterminal m to obtain estimates of the complex channel gain betweenaccess point antenna i and each of the N_(ut,m) user terminal antennas.The covering at the user terminal and the decovering at the access pointcan be performed in similar manner as for a Code Division MultipleAccess (CDMA) system. For frequency orthogonality, the N_(ut,m) pilottransmissions for the N_(ut,m) user terminal antennas can be sentsimultaneously on different subbands of the overall system bandwidth.For time orthogonality, the N_(ut,m) pilot transmissions for theN_(ut,m) user terminal antennas can be sent in different time slots. Inany case, the orthogonality among the N_(ut,m) pilot transmissionsallows the access point to distinguish the pilot transmission from eachuser terminal antenna.

Multiple user terminals can simultaneously transmit unsteered pilots onthe uplink to the access point. The pilot transmissions for all userterminals are orthogonal in code, time, and/or frequency to allow theaccess point to estimate the uplink channel response for each userterminal.

In a TDD system, the downlink and uplink share the same frequency band.A high degree of correlation normally exists between the downlink anduplink channel responses. However, the responses of the transmit/receivechains at the access point may not be the same as the responses of thetransmit/receive chains at the user terminal. If the differences can bedetermined via calibration and accounted for by applying the propercorrection matrices at the access point and/or user terminal, then theoverall downlink and uplink channel responses may be assumed to bereciprocal (i.e., transpose) of each other.

For the TDD system, the access point can transmit an unsteered pilotfrom N_(ap) access point antennas. Each user terminal m can (1) processthe downlink unsteered pilot to obtain its downlink MIMO channelresponse matrix H _(dn,m), (2) estimate the uplink MIMO channel responseas the transpose of the downlink MIMO channel response (i.e., H_(up,m)≅H _(dn,m) ^(T)), (3) derive the steering vector v _(up,m) or{tilde over (v)} _(up,m) based on H _(up,m), and (4) compute theeffective uplink channel response vector h _(up,eff,m). Each userterminal can send the vector h _(up,eff,m) to the access point in adirect form (e.g., by sending the entries of h _(up,eff,m)) or anindirect form (e.g., by transmitting a steered pilot that is generatedwith the steering vector v _(up,m) or {tilde over (v)} _(up,m) used foruplink transmission).

For clarity, the SDMA transmission techniques have been described foruplink transmission. These techniques may also be used for downlinktransmission. A downlink MIMO channel response matrix H _(dn,m) can beobtained for each user terminal m and decomposed to obtain a downlinksteering vector v _(dn,m) for the user terminal. The access point canevaluate different sets of user terminals for downlink transmission(e.g., in similar manner as that described above for the uplink) andselect the best set of N_(dn) user terminals for downlink transmission.

For downlink transmission, the access point spatially processes N_(dn)data symbol streams with N_(dn) downlink steering vectors for the N_(dn)selected user terminals to obtain N_(ap) transmit symbol streams, asfollows:

x _(dn) =V _(dn) ·s _(dn),   Eq (22)

where s _(dn) is an N_(dn)×1 vector with N_(dn) data symbols to betransmitted on the downlink to the N_(dn) selected user terminals;

-   -   V _(dn) is an N_(ap)×N_(dn) matrix with N_(dn) downlink steering        vectors for the N_(dn) selected user terminals, which is V        _(dn)=[v _(dn,1) v _(dn,2) . . . v _(dn,N) _(dn) ]; and    -   x _(dn) is an N_(ap)×1 vector with N_(ap) transmit symbols to be        sent from the N_(ap) access point antennas.        The access point may also spatially process the downlink data        symbol stream for each user terminal with a normalized downlink        steering vector {tilde over (v)} _(dn,m) for beam-steering.

If a user terminal is equipped with at least N_(ap) antennas (i.e.,N_(ut,m)≧N_(ap)), then the user terminal can perform receiver spatialprocessing using CCMI, MMSE, or some other technique to isolate andrecover its downlink data symbol stream. If a user terminal is equippedwith less than N_(ap) antennas (i.e., N_(ut,m)<N_(ap)), then the userterminal can recover its downlink data symbol stream in the presence ofcrosstalk from the other data symbol streams.

For clarity, the SDMA transmission techniques have been described for asingle-carrier narrowband MIMO system with flat-fading. These techniquesmay also be used for a wideband MIMO system and a multi-carrier MIMOsystem. A wideband MIMO system may utilize CDMA as the underlyingwireless technology. A multi-carrier MIMO system may utilize OFDM orsome other multi-carrier modulation technique. OFDM effectivelypartitions the overall system bandwidth into multiple (N_(F)) orthogonalsubbands. Each subband is associated with a respective carrier that maybe modulated with data.

For a MIMO OFDM system, for each user terminal, the channel estimationmay be performed for each of the N_(F) subbands to obtain N_(F)frequency-domain channel response matrices for the N_(F) subbands. Thespatial processing may be performed in various manners. In oneembodiment, each of the N_(F) channel response matrices is independentlydecomposed to obtain N_(F) steering vectors for the N_(F) subbands.Spatial processing is then performed for each subband with the steeringvector obtained for that subband. In another embodiment, a singlefrequency-independent steering vector is derived for each user terminalbased on the N_(F) channel response matrices. Spatial processing is thenperformed for all N_(F) subbands with this single steering vector. Inany case, N_(F) effective uplink channel response vectors h_(up,eff,m)(k), for k=1 . . . N _(F), are formed for each user terminalwith either the single or N_(F) steering vectors. The user terminals maybe evaluated based on their frequency-dependent effective channelresponse vectors.

For a wideband MIMO system, for each user terminal, a time-domainchannel impulse response matrix may be obtained for each of multiple(N_(P)) resolvable signal paths in the MIMO channel. In one embodiment,N_(P) steering vectors are derived for each user terminal based on theN_(P) channel impulse response matrices and used to account for thefrequency-selective nature of the MIMO channel. In another embodiment,one steering vector is derived for each user terminal, for example,based on the channel impulse response matrix for the main signal pathwith the highest energy. In any case, the steering vector(s) may be usedto derive one or more effective channel response vectors, which are inturn used to evaluate and select user terminals for transmission.

4. Exemplary MIMO System

FIG. 4 shows a block diagram of access point 110 and two user terminals120 m and 120 x in MIMO system 100. Access point 110 is equipped withNap antennas 424 a through 424 ap. User terminal 120 m is equipped withN_(ut,m) antennas 452 ma through 452 mu, and user terminal 120 x isequipped with N_(ut,x) antennas 452 xa through 452 xu. Access point 110is a transmitting entity for the downlink and a receiving entity for theuplink. Each user terminal 120 is a transmitting entity for the uplinkand a receiving entity for the downlink. As used herein, a “transmittingentity” is an independently operated apparatus or device capable oftransmitting data via a wireless channel, and a “receiving entity” is anindependently operated apparatus or device capable of receiving data viaa wireless channel. In the following description, the subscript “dn”denotes the downlink, the subscript “up” denotes the uplink, N_(up) userterminals are selected for simultaneous transmission on the uplink,N_(dn) user terminals are selected for simultaneous transmission on thedownlink, N_(up) may or may not be equal to N_(dn), and N_(up) andN_(dn) may be static values or can change for each scheduling interval.For simplicity, beam-steering is used in the following description.

On the uplink, at each user terminal 120 selected for uplinktransmission, a TX data processor 488 receives traffic data from a datasource 486 and control data from a controller 480. TX data processor 488processes (e.g., encodes, interleaves, and modulates) the traffic data{d_(up,m)} for the user terminal based on the coding and modulationschemes associated with the rate selected for the user terminal andprovides a data symbol stream {s_(up,m)}. A TX spatial processor 490performs spatial processing on the data symbol stream {s_(up,m)} withthe steering vector v _(up,m), multiplexes in pilot symbols as needed,and provides N_(ut,m) transmit symbol streams for the N_(ut,m) antennas.The steering vector v _(up,m) is derived based on the uplink channelresponse matrix H _(up,m) for the user terminal, as described above.Each transmitter unit (TMTR) 454 receives and processes (e.g., convertsto analog, amplifies, filters, and frequency upconverts) a respectivetransmit symbol stream to generate an uplink signal. N_(ut,m)transmitter units 454 provide N_(ut,m) uplink signals for transmissionfrom N_(ut,m) antennas 452 to the access point.

N_(up) user terminals may be scheduled for simultaneous transmission onthe uplink. Each of these user terminals performs spatial processing onits data symbol stream with its steering vector and transmits its set oftransmit symbol streams on the uplink to the access point.

At access point 110, Nap antennas 424 a through 424 ap receive theuplink signals from all N_(up) user terminals transmitting on theuplink. Each antenna 424 provides a received signal to a respectivereceiver unit (RCVR) 422. Each receiver unit 422 performs processingcomplementary to that performed by transmitter unit 454 and provides areceived symbol stream. An RX spatial processor 440 performs receiverspatial processing on the Nap received symbol streams from Nap receiverunits 422 and provides N_(up) recovered uplink data symbol streams. Thereceiver spatial processing is performed in accordance with the CCMI,MMSE, SIC, or some other technique. A spatial filter matrix M _(ap) forthe access point is derived based on (1) the receiver spatial processingtechnique used by the access point and (2) the effective uplink channelresponse matrix H _(up,eff) for the N_(up) user terminals. Eachrecovered uplink data symbol stream {ŝ_(up,m)} is an estimate of a datasymbol stream {s_(up,m)} transmitted by a respective user terminal. AnRX data processor 442 processes (e.g., demodulates, deinterleaves, anddecodes) each recovered uplink data symbol stream {ŝ_(up,m)} inaccordance with the rate used for that stream to obtain decoded data.The decoded data for each user terminal may be provided to a data sink444 for storage and/or a controller 430 for further processing.

On the downlink, at access point 110, a TX data processor 410 receivestraffic data from a data source 408 for N_(dn) user terminals scheduledfor downlink transmission, control data from a controller 430, andpossibly other data from a scheduler 434. The various types of data maybe sent on different transport channels. TX data processor 410 processes(e.g., encodes, interleaves, and modulates) the traffic data for eachuser terminal based on the rate selected for that user terminal. TX dataprocessor 410 provides N_(dn) downlink data symbol streams for theN_(dn) user terminals. A TX spatial processor 420 performs spatialprocessing on the N_(dn) downlink data symbol streams with a matrix V_(dn) of N_(dn) downlink steering vectors for the N_(dn) user terminals,multiplexes in pilot symbols, and provides Nap transmit symbol streamsfor the Nap antennas. Each transmitter unit 422 receives and processes arespective transmit symbol stream to generate a downlink signal. Naptransmitter units 422 provide Nap downlink signals for transmission fromNap antennas 424 to the user terminals.

At each user terminal 120, N_(ut,m) antennas 452 receive the Napdownlink signals from access point 110. Each receiver unit 454 processesa received signal from an associated antenna 452 and provides a receivedsymbol stream. An RX spatial processor 460 performs receiver spatialprocessing on N_(ut,m) received symbol streams from N_(ut,m) receiverunits 454 and provides a recovered downlink data symbol stream{ŝ_(dn,m)} for the user terminal. The receiver spatial processing isperformed in accordance with the CCMI, MMSE, or some other technique. Aspatial filter matrix M _(ut,m) for each user terminal is derived basedon (1) the receiver spatial processing technique used by the userterminal and (2) the downlink channel response matrix H _(dn,m) for theuser terminal. An RX data processor 470 processes (e.g., demodulates,deinterleaves, and decodes) the recovered downlink data symbol stream toobtain decoded data for the user terminal.

At each user terminal 120, a channel estimator 478 estimates thedownlink channel response and provides downlink channel estimates, whichmay include channel gain estimates, SNR estimates, and so on. Similarly,a channel estimator 428 estimates the uplink channel response andprovides uplink channel estimates. The steering vectors for downlink anduplink transmission may be derived in various manners depending onwhether the MIMO system is a TDD system or an FDD system, as describedabove. If the steering vector is derived by one entity (e.g., the accesspoint) and needed by another entity (e.g., the user terminal), then theone entity sends the steering vector to the other entity.

Controller 480 for each user terminal typically derives the spatialfilter matrix M _(ut,m) for the user terminal based on the downlinkchannel response matrix H _(dn,m) for that user terminal. Controller 430derives the spatial filter matrix M _(ap) for the access point based onthe effective uplink channel response matrix H _(up,eff). Controller 480for each user terminal may send feedback information (e.g., the downlinkand/or uplink steering vectors, SNR estimates, and so on) to the accesspoint. Controllers 430 and 480 also control the operation of variousprocessing units at access point 110 and user terminal 120,respectively.

FIG. 5A shows a block diagram of a TX data processor 410 a that supportsCDMA. TX data processor 410 a may be used for TX data processors 410 and488 in FIG. 4. Within TX data processor 410 a, an encoder 512 receivesand codes a data stream {d_(m)} for user terminal m based on the codingscheme for the selected rate and provides code bits. The data stream maycarry one or more data packets, and each data packet is typically codedseparately to obtain a coded data packet. The coding increases thereliability of the data transmission. The coding scheme may includecyclic redundancy check (CRC) coding, convolutional coding, turbocoding, block coding, and so on, or a combination thereof. A channelinterleaver 514 interleaves the code bits based on an interleavingscheme. The interleaving provides time, frequency, and/or spatialdiversity for the code bits. A symbol mapping unit 516 maps theinterleaved bits based on the modulation scheme for the selected rateand provides data symbols. Unit 516 groups each set of B interleavedbits to form a B-bit binary value, where B≧1, and further maps eachB-bit value to a specific modulation symbol based on the modulationscheme (e.g., QPSK, M-PSK, or M-QAM, where M=2^(B)). Each modulationsymbol is a complex value in a signal constellation defined by themodulation scheme.

A CDMA modulator 520 performs modulation for CDMA. Within CDMA modulator520, a channelizer 522 receives and channelizes the data symbols andpilot symbols onto different code channels. Each code channel isassociated with a respective orthogonal sequence, which may be a Walshsequence, an orthogonal variable spreading factor (OVSF) sequence, andso on. The channelization is referred to as “covering” in IS-2000 andIS-95 and “spreading” in W-CDMA. A scrambler 524 receives and spectrallyspreads the channelized data for multiple code channels with apseudo-random number (PN) sequence and provides a stream of data chips,which for simplicity is denoted as a data symbol stream {s_(m)}. Thespectral spreading is referred to as “spreading” in IS-2000 and IS-95and “scrambling” in W-CDMA. The channelization and spectral spreadingare known in the art and not described herein.

For the uplink, each data symbol stream is transmitted on a respectivecode channel, which is achieved by channelization with an orthogonalsequence. The Nup selected user terminals may concurrently transmitN_(up) or more data streams on different orthogonal code channels. Eachuser terminal performs spatial processing on all of its data symbolstreams (or its data chip stream) with the same steering vector v_(up,m) or {tilde over (v)} _(up,m). Similar processing occurs for thedownlink.

FIG. 5B shows a block diagram of a TX data processor 410 b that supportsOFDM. TX data processor 410 b may also be used for TX data processors410 and 488 in FIG. 4. TX data processor 410 b includes encoder 512,channel interleaver 514, and symbol mapping unit 516, which operate asdescribed above for FIG. 5A. TX data processor 410 b further includes anOFDM modulator 530 that performs modulation for OFDM. Within OFDMmodulator 530, an inverse fast Fourier transform (IFFT) unit 532receives the data symbols from symbol mapping unit 516 and pilotsymbols, provides the data and pilot symbols on subbands designated fordata and pilot transmission, and provides a signal value of zero (a“zero” symbol) for each subband not used for data/pilot transmission.For each OFDM symbol period, IFFT unit 532 transforms a set of NF data,pilot, and zero symbols to the time domain using an NF-point inversefast Fourier transform and provides a corresponding transformed symbolthat contains NF chips. A cyclic prefix generator 534 repeats a portionof each transformed symbol to obtain a corresponding OFDM symbol thatcontains N_(F)+N_(cp) chips. The repeated portion is referred to as acyclic prefix, and N_(cp) is the number of chips being repeated. Thecyclic prefix ensures that the OFDM symbol retains its orthogonalproperties in the presence of multipath delay spread caused by frequencyselective fading (i.e., a frequency response that is not flat). Cyclicprefix generator 534 provides a stream of OFDM symbols, which forsimplicity is also denoted as a data symbol stream {s_(m)}.

For the uplink, each data symbol stream is transmitted on a respectiveset of subbands assigned for that stream. The N_(up) selected userterminals may concurrently transmit N_(up) or more data streams ondifferent disjoint sets of subbands, where each of the NF subbands isassigned to at most one set. Each user terminal performs spatialprocessing on all of its data symbol streams (or its OFDM symbol stream)with the same steering vector v _(up,m) or {tilde over (v)} _(up,m).Similar processing occurs for the downlink.

For simplicity, FIGS. 5A and 5B show the processing for one data stream{d_(m)} to obtain one data symbol steam {s_(m)}. Multiple data steams(e.g., for multiple user terminals on the downlink) may be processedwith multiple instances of the TX data processor to obtain multiple datasymbol steams.

FIGS. 5A and 5B show specific implementations in which the processingfor CDMA and OFDM are performed prior to the spatial processing formulti-antenna transmission. In this case, the TX data processor includesthe CDMA modulator or OFDM modulator, as shown in FIGS. 5A and 5B. Theprocessing for CDMA and OFDM may also be performed after the spatialprocessing for multi-antenna transmission. In this case, eachtransmitter unit (TMTR) would include a CDMA modulator or an OFDMmodulator that performs CDMA or OFDM processing on a respective transmitsymbol stream to generate a corresponding modulated signal.

FIG. 6 shows the spatial processing at access point 110 and one userterminal 120 m for downlink and uplink transmission. For the uplink, atuser terminal 120 m, the data symbol stream {s_(up,m)} is multipliedwith the steering vector v _(up,m) by TX spatial processor 490 m toobtain the transmit symbol vector x _(up,m) for the uplink. At accesspoint 110, the received symbol vector r _(up) (for user terminal 120 mas well as other user terminals) is multiplied with a spatial filtermatrix M _(ap) by a unit 640 and further scaled with a diagonal matrix D_(ap) ⁻¹ by a unit 642 to obtain the recovered data symbol vector {tildeover (s)} _(up) for the uplink. Units 640 and 642 are part of an RXspatial processor 440 a. The matrices M _(ap) and D _(ap) ⁻¹ are derivedbased on the effective uplink channel response matrix H _(up,eff) andusing the CCMI, MMSE, or some other technique.

For the downlink, at access point 110, the data symbol vector s _(dn)(which includes the downlink data symbol streams for user terminal 120 mas well as other user terminals) is multiplied with the downlinksteering matrix V _(dn) by TX spatial processor 420 to obtain thetransmit symbol vector x _(dn) for the downlink. At user terminal 120 m,the received symbol vector r _(dn,m) is multiplied with a spatial filtermatrix M _(ut,m) by a unit 660 and further scaled with a diagonal matrixD _(ut,m) ⁻¹ by a unit 662 to obtain a downlink recovered data symbolstream {ŝ_(dn,m)} for user terminal 120 m. Units 660 and 662 are part ofRX spatial processor 460 m. The matrices M _(ut,m) and D _(ut,m) ⁻¹ arederived based on the downlink channel response matrix H _(dn,m) for userterminal 120 m and using the CCMI, MMSE, or some other technique.

FIG. 7 shows a block diagram of an RX spatial processor 440 b and an RXdata processor 442 b, which implement the SIC technique and may be usedfor access point 110. RX spatial processor 440 b and RX data processor442 b implement N_(up) successive (i.e., cascaded) receiver processingstages for N_(up) data symbol streams transmitted by N_(up) userterminals. Each of stages 1 to N_(up)−1 includes a spatial processor710, an interference canceller 720, an RX data stream processor 730, anda TX data stream processor 740. The last stage includes only a spatialprocessor 710 u and an RX data stream processor 730 u.

For stage 1, spatial processor 710 a performs receiver spatialprocessing on the Nap received symbol streams and provides one recovereddata symbol stream {ŝ_(up,j) ₁ } for user terminal j1 being recovered inthe first stage. RX data stream processor 730 a demodulates,deinterleaves, and decodes the recovered data symbol stream {ŝ_(up,j) ₁} and provides a decoded data stream {{circumflex over (d)}_(up,j) ₁ }.TX data stream processor 740 a encodes, interleaves, and modulates thedecoded data stream {{circumflex over (d)}_(up,j) ₁ } in the same mannerperformed by user terminal j1 for that stream and provides a remodulatedsymbol stream {{hacek over (s)}_(up,j) ₁ }. Interference canceller 720 aperforms transmitter spatial processing on the remodulated symbol stream{{hacek over (s)}_(up,j) ₁ } with the effective channel response vectorh _(up,eff,j) ₁ for user terminal j1 to obtain Nap interferencecomponents due to the data symbol stream {s_(up,j) ₁ }. The Napinterference components are subtracted from the Nap received symbolstreams to obtain Nap modified symbol streams, which are provided tostage 2.

Each of stages 2 through N_(up)−1 performs the same processing as stage1, albeit on the Nap modified symbol streams from the preceding stageinstead of the Nap received symbol streams. The last stage performsspatial processing and decoding on the Nap modified symbol streams fromstage N_(up)−1 and does not perform interference estimation andcancellation.

Spatial processors 710 a through 710 u may each implement the CCMI,MMSE, or some other technique. Each spatial processor 710 multiplies aninput (received or modified) symbol vector r _(sic) ^(l) with a spatialfilter matrix M _(ap) ^(l) to obtain a detected symbol vector {tildeover (s)} _(up) ^(l), selects and scales one of the detected symbolstreams, and provides the scaled symbol stream as the recovered datasymbol stream for that stage. The matrix M _(ap) ^(l) is derived basedon a reduced effective channel response matrix H _(up,eff) ^(l) for thestage.

FIG. 8 shows a block diagram of an embodiment of controller 430 andscheduler 434 for evaluating and scheduling user terminals fortransmission on the downlink and uplink. Within controller 430, arequest processor 810 receives access requests sent by user terminals120 and possibly access requests from other sources. These accessrequests are for data transmission on the downlink and/or uplink. Forclarity, scheduling for uplink transmission is described below.

Request processor 810 processes the received access requests andprovides the identities (IDs) and the status of all active userterminals. A user selector 820 selects different sets of user terminalsfrom among all active user terminals for evaluation. The user terminalsmay be selected for evaluation based on various factors such as userpriority, the amount of data to send, system requirements, and so on.

An evaluation unit 830 evaluates each set of user terminals and providesa value for a metric for the set. For simplicity, the followingdescription assumes that (1) overall throughput is used as the metricand (2) the effective uplink channel response vector is available foreach active user terminal. Evaluation unit 830 includes a matrixcomputation unit 840 and a rate selector 850. Matrix computation unit840 performs the SNR computation for each set of user terminals. Foreach set, unit 840 forms the effective uplink channel response matrix H_(up,eff,n) for the set and computes the SNR for each user terminal inthe set based on H _(up,eff,n) and the receiver spatial processingtechnique used by the access point. Rate selector 850 receives a set ofSNRs for each user set and determines the rate for each user terminal inthe set as well as the overall throughput R_(n) for the set. Rateselector 850 may access a look-up table (LUT) 852, which stores a set ofrates supported by the system and their required SNRs. Rate selector 850determines the highest rate that may be used for uplink transmission byeach user terminal based on the SNR computed for the user terminal. Rateselector 850 also accumulates the rates or throughputs for all userterminals in each set to obtain the overall throughput R_(n) for theset.

Scheduler 434 receives (1) the different sets of user terminals fromuser selector 820 and (2) the rates for the user terminals and theoverall throughput for each set from rate selector 850. Scheduler 434selects the best set of user terminals among all sets evaluated for eachscheduling interval and schedules the selected user terminals fortransmission on the uplink. Scheduler 434 provides schedulinginformation, which includes the identities of the selected userterminals, their rates, the scheduled transmission time (e.g., the startand the duration of the transmission), and so on. The schedulinginformation is sent to the selected user terminals.

The scheduling for downlink transmission may be performed in similarmanner.

The SDMA transmission techniques described herein may be implemented byvarious means. For example, these techniques may be implemented inhardware, software, or a combination thereof. For a hardwareimplementation, the processing units used to support the underlyingwireless technology (e.g., CDMA or OFDM) and the SDMA transmission onthe downlink and uplink (e.g., the transmit and receive spatialprocessing at the access point and user terminal, the evaluation ofdifferent user sets, and so on) may be implemented within one or moreapplication specific integrated circuits (ASICs), digital signalprocessors (DSPs), digital signal processing devices (DSPDs),programmable logic devices (PLDs), field programmable gate arrays(FPGAs), processors, controllers, micro-controllers, microprocessors,other electronic units designed to perform the functions describedherein, or a combination thereof.

For a software implementation, the SDMA transmission techniquesdescribed herein may be implemented with modules (e.g., procedures,functions, and so on) that perform the functions described herein. Thesoftware codes may be stored in a memory unit (e.g., memory units 432and 482 in FIG. 4) and executed by a processor (e.g., controllers 430and 480). The memory unit may be implemented within the processor orexternal to the processor, in which case it can be communicativelycoupled to the processor via various means as is known in the art.

Headings are included herein for reference and to aid in locatingcertain sections. These headings are not intended to limit the scope ofthe concepts described therein under, and these concepts may haveapplicability in other sections throughout the entire specification.

The previous description of the disclosed embodiments is provided toenable any person skilled in the art to make or use the presentinvention. Various modifications to these embodiments will be readilyapparent to those skilled in the art, and the generic principles definedherein may be applied to other embodiments without departing from thespirit or scope of the invention. Thus, the present invention is notintended to be limited to the embodiments shown herein but is to beaccorded the widest scope consistent with the principles and novelfeatures disclosed herein.

1. A method of receiving data in a multiple-input multiple-output (MIMO)communication system, comprising: obtaining, from a plurality of receiveantennas at a receiving entity, a plurality of received symbol streamsfor a plurality of data symbol streams sent by a plurality oftransmitting entities, one data symbol stream for each transmittingentity, wherein the data symbol stream for each transmitting entity isspatially processed with a steering vector for the transmitting entityand sent from a plurality of transmit antennas at the transmittingentity; and wherein the steering vector for each transmitting entity isderived by: decomposing a channel response matrix for the transmittingentity to obtain a plurality of eigenvectors and a plurality of singularvalues, and forming the steering vector for the transmitting entitybased on an eigenvector corresponding to a largest singular value amongthe plurality of singular values.
 2. The method of claim 1, furthercomprising: processing the plurality of received symbol streams inaccordance with a receiver spatial processing technique to obtain aplurality of recovered data symbol streams, which are estimates of theplurality of data symbol streams.
 3. The method of claim 2, wherein thereceiver spatial processing technique is a channel correlation matrixinversion (CCMI) technique or a minimum mean square error (MMSE)technique.
 4. The method of claim 2, wherein the receiver spatialprocessing technique is a successive interference cancellation (SIC)technique.
 5. The method of claim 1, wherein the steering vector foreach transmitting entity is equal to the eigenvector corresponding tothe largest singular value.
 6. An apparatus at a receiving entity in amultiple-input multiple-output (MIMO) communication system, comprising:a plurality of receiver units operative to obtain from a plurality ofreceive antennas a plurality of received symbol streams for a pluralityof data symbol streams sent by a plurality of transmitting entities, onedata symbol stream for each transmitting entity, wherein the data symbolstream for each transmitting entity is spatially processed with asteering vector for the transmitting entity and sent from a plurality oftransmit antennas at the transmitting entity; and wherein the steeringvector for each transmitting entity is derived by: decomposing a channelresponse matrix for the transmitting entity to obtain a plurality ofeigenvectors and a plurality of singular values, and forming thesteering vector for the transmitting entity based on an eigenvectorcorresponding to a largest singular value among the plurality ofsingular values.
 7. The apparatus of claim 6, further comprising: areceive spatial processor operative to process the plurality of receivedsymbol streams in accordance with a receiver spatial processingtechnique to obtain a plurality of recovered data symbol streams, whichare estimates of the plurality of data symbol streams.
 8. The apparatusof claim 7, wherein the receiver spatial processing technique is achannel correlation matrix inversion (CCMI) technique or a minimum meansquare error (MMSE) technique.
 9. The apparatus of claim 7, wherein thereceiver spatial processing technique is a successive interferencecancellation (SIC) technique.
 10. The apparatus of claim 6, wherein thesteering vector for each transmitting entity is equal to the eigenvectorcorresponding to the largest singular value.
 11. An apparatus at areceiving entity in a multiple-input multiple-output (MIMO)communication system, comprising: means for obtaining from a pluralityof receive antennas a plurality of received symbol streams for aplurality of data symbol streams sent by a plurality of transmittingentities, one data symbol stream for each transmitting entity, whereinthe data symbol stream for each transmitting entity is spatiallyprocessed with a steering vector for the transmitting entity and sentfrom a plurality of transmit antennas at the transmitting entity; andwherein the steering vector for each transmitting entity is derived by:decomposing a channel response matrix for the transmitting entity toobtain a plurality of eigenvectors and a plurality of singular values,and forming the steering vector for the transmitting entity based on aneigenvector corresponding to a largest singular value among theplurality of singular values.
 12. The apparatus of claim 11, furthercomprising: means for processing the plurality of received symbolstreams in accordance with a receiver spatial processing technique toobtain a plurality of recovered data symbol streams, which are estimatesof the plurality of data symbol streams.
 13. The apparatus of claim 12,wherein the receiver spatial processing technique is a channelcorrelation matrix inversion (CCMI) technique or a minimum mean squareerror (MMSE) technique.
 14. The apparatus of claim 12, wherein thereceiver spatial processing technique is a successive interferencecancellation (SIC) technique.
 15. The apparatus of claim 11, wherein thesteering vector for each transmitting entity is equal to the eigenvectorcorresponding to the largest singular value.
 16. A computer-programproduct at a receiving entity in a multiple-input multiple-output (MIMO)communication system comprising a computer readable medium havinginstructions thereon, the instructions comprising: code for obtainingfrom a plurality of receive antennas a plurality of received symbolstreams for a plurality of data symbol streams sent by a plurality oftransmitting entities, one data symbol stream for each transmittingentity, wherein the data symbol stream for each transmitting entity isspatially processed with a steering vector for the transmitting entityand sent from a plurality of transmit antennas at the transmittingentity; and wherein the steering vector for each transmitting entity isderived by: decomposing a channel response matrix for the transmittingentity to obtain a plurality of eigenvectors and a plurality of singularvalues, and forming the steering vector for the transmitting entitybased on an eigenvector corresponding to a largest singular value amongthe plurality of singular values.
 17. The computer-program product ofclaim 16, further comprising: code for processing the plurality ofreceived symbol streams in accordance with a receiver spatial processingtechnique to obtain a plurality of recovered data symbol streams, whichare estimates of the plurality of data symbol streams.
 18. Thecomputer-program product of claim 17, wherein the receiver spatialprocessing technique is a channel correlation matrix inversion (CCMI)technique or a minimum mean square error (MMSE) technique.
 19. Thecomputer-program product of claim 17, wherein the receiver spatialprocessing technique is a successive interference cancellation (SIC)technique.
 20. The computer-program product of claim 16, wherein thesteering vector for each transmitting entity is equal to the eigenvectorcorresponding to the largest singular value.